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Trexquant

Quantitative trading via ML models

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeBeijing, ChinaNo salary listedHybrid

About the Job

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
  • At least 2 years of data engineering experience within a systematic trading, quantitative research, hedge fund, or financial technology environment.
  • Python and SQL development experience building large-scale data ingestion and extract, transform, and load (ETL) pipelines.
  • Strong Linux experience, including scripting, automation, and operating production data processing systems.
  • Deep knowledge of financial data across multiple asset classes, including equities, options, futures, fixed income, exchange-traded funds, foreign exchange, and alternative datasets.
  • Experience with market data, tick data, reference data, and vendor data feeds, including normalization, validation, and quality control.
  • Familiarity with modern data storage formats and technologies such as Parquet, Arrow, object storage, and columnar databases.
  • Fluency in English.

Responsibilities

  • Design, build, and maintain scalable ingestion pipelines for market, reference, tick, and alternative data from external vendors.
  • Own the normalization, validation, storage, and lifecycle management of research datasets, ensuring data is accurate, consistent, and accessible for quantitative research and simulation.
  • Develop and optimize Python- and SQL-based data processing workflows supporting equities, options, futures, fixed income, exchange-traded funds, and foreign exchange.
  • Partner with quantitative researchers, data architects, and infrastructure teams to onboard datasets, improve data quality, and deliver research-ready data.
  • Build monitoring, automation, and operational tooling to ensure the reliability, performance, and scalability of the firm's data platform.
  • Document data pipelines and engineering best practices while contributing to the evolution of the firm's research data infrastructure.

About the Company

Trexquant

Quantitative trading via ML models

Trexquant is a quantitative finance firm that builds multi-asset portfolios using machine learning. It develops investment and research tools that ingest a wide range of data variables to create complex trading models and strategies, which in turn generate trading signals. These signals guide decisions across global markets. The product works by applying advanced machine learning to large datasets to create predictive models and rule-based strategies, which drive portfolio construction and trading actions through the firm’s platform. Trexquant differentiates itself by emphasizing the breadth of data it uses and the depth of machine-learning driven models to craft multi-asset portfolios, aiming to produce signals that outperform global market conditions. The company’s goal is to generate investment performance that beats benchmarks by using data-driven signals and diversified, multi-asset strategies.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Stamford, CT
Founded
2012

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